I am interested in artificial intelligence in general, and in its uses
within medical domains in particular. More specifically, I am interested in
temporal reasoning and planning in general, and in clinical decision-support
applications in particular. I am also interested in general methods for
knowledge representation and knowledge acquisition, and in general, in reusable
and sharable, problem-solving methods. Apart from classical artificial
intelligence techniques, I am also interested in applications of theoretical
computer science techniques to such problems. I also have an interest in
medical decision analysis.

A task common to many application domains is the analysis of data accumulated
over time, leading to identification of past and present trends and to episodic
decisions made on the basis of the previous and the current state of the world.
An example of such a task in the medical domain is managing patients who are
being treated with clinical guidelines. An inherent requirement of such tasks
is to accumulate and to analyze patient data over time and constantly to revise
an assessment of the patient's state by abstracting higher-level,
context-sensitive concepts from the raw input data. These higher-level concepts
can be used for summarizing large medical databases, for monitoring, for
replanning therapy, for providing explanations to a user of a decision-support
system, for (temporal) data mining and knowledge discovery, and as a basis for a more intelligent dialog between an automated
decision-support system and a human health-care provider.

My work focuses on defining basic knowledge-based, domain-independent
temporal-abstraction mechanisms and the formal knowledge needed to instantiate
them in any particular medical domain. Formalization of temporal-abstraction
knowledge supports the acquisition, representation, maintenance, reuse, and
sharing of that knowledge. I have therefore defined a knowlede-based
temporal-abstraction framework, implemented it as the
RÉSUMÉ system, and tested it in several clinical
domains. The framework has been expanded and embedded in a larger architecture,
Tzolkin, which combines temporal-reasoning and temporal-maintenance
services. Tzolkin had been used within the
EON component-based architecure for guideline-based care. An extension
of Tzolkin is the
IDAN temporal mediator at Ben Gurion University's
Medical Informatics Research Center
.

I also am interested in (therapy) plan generation, revision, recognition and
critiquing in clinical domains; I have previously set up the Asgaard
project, ongoing in several countries, which investigates these tasks. I am also leading the
Digital Electronic Guideline Library (DeGeL) project, which creates a distributed
framework for specification, retrieval, and use of clinical guidelines.

Finally, I am interested in decision-theoretical aspects of clinical decision
making. I have previously led the PANDA
project at Stanford University, which applied decision analytic methodologies to the domain of genetic
consultation, taking into account the patient's characteristics and personal
preferences, and the
PANDEX
project at BGU, which has implemented these methodologies on the WEB and
investigated seevral methods for sensitivity analysis of the recommended optimal
decision.
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